Job
Description
Job Summary We are looking for a Senior Analytics Engineer to drive data excellence and innovation in our organization. As a thought leader in data engineering and analytics principles , you will be responsible for designing, building, and optimizing our data infrastructure while ensuring cost efficiency, security, and scalability . You will play a crucial role in managing Databricks and AWS usage , ensuring budget adherence, and taking proactive measures to optimize costs. This role also requires expertise in ETL processes, large-scale data processing, analytics, and data-driven decision-making , along with strong analytical and leadership skills. Responsibilities Act as a thought leader in data engineering and analytics, driving best practices and standards. Oversee cost management of Databricks and AWS, ensuring resource usage stays within allocated budgets and taking corrective actions when necessary. Design, implement, and optimize ETL pipelines for incremental data loading, ensuring seamless data ingestion, transformation, and performance tuning. Lead migration activities, ensuring smooth transitions while maintaining data integrity and availability. Handle massive data loads efficiently, optimizing storage, compute usage, and query performance. Adhere to Git principles for version control, ensuring best practices for collaboration and deployment. Implement and manage DSR (Airflow) workflows to automate and schedule data pipelines efficiently. Ensure data security and compliance, especially when handling PII data, aligning with regulations like GDPR and HIPAA. Optimize query performance and data storage strategies to improve cost efficiency and speed of analytics. Collaborate with data analysts and business stakeholders to enhance analytics capabilities, enabling data-driven decision-making. Develop and maintain dashboards, reports, and analytical models to provide actionable insights for business and engineering teams. Required Skills & Qualifications Four-year or Graduate Degree in Computer Science, Information Systems, or any other related discipline or commensurate work experience or demonstrated competence. 6-11 years of experience in Data Engineering, Analytics, Big Data, or related domains. Strong expertise in Databricks, AWS (S3, EC2, Lambda, RDS, Redshift, Glue, etc.), and cost optimization strategies. Hands-on experience with ETL pipelines, incremental data loads, and large-scale data processing. Proven experience in analyzing large datasets, deriving insights, and optimizing data workflows. Strong knowledge of SQL, Python, PySpark, and other data engineering and analytics tools. Strong problem-solving, analytical, and leadership skills. Experience with BI tools like Tableau, Looker, or Power BI for data visualization and reporting. Preferred Certifications Certified Software Systems Engineer (CSSE) Certified Systems Engineering Professional (CSEP) Cross-Org Skills Effective Communication Results Orientation Learning Agility Digital Fluency Customer Centricity Impact & Scope Impacts function and leads and/or provides expertise to functional project teams and may participate in cross-functional initiatives. Complexity Works on complex problems where analysis of situations or data requires an in-depth evaluation of multiple factors. Disclaimer This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management. Show more Show less
